The present invention relates generally to mobile communications, and, more particularly, to two-stream receivers for multiple-input multiple-output MIMO systems and their extensions.
In order to meet the ambitious spectral efficiency targets set for Evolved-UMTS Terrestrial Radio Access (EUTRA), low-latency and low complexity receivers are necessary. Such receivers are particularly needed at the user equipment (UE) where the complexity constraints are much more stringent. The most important scenario in the multiple antenna downlink system involves UEs with two antennas, where the base-station or the Node-B transmits two encoded streams to a scheduled UE.
A known brute force maximum likelihood ML reception method 10 for two streams, depicted in FIG. 1, involves listing all possible pairs for symbols 1 and 2 11, evaluating the metric for each pair 12, using the metrics to determine the exact max-log LLRs (maximum log likelihood ratios) for all the bits 13 and decoding the codeword(s) using the computing LLRs 14. Although the brute force ML method provides optimal demodulation it is highly complex.
The main competing demodulators to the invention are the Deterministic Sequential Monte-Carlo (D-SMC) based receiver (another promising low-complexity receiver), shown in FIG. 2, and the successive interference cancellation SIC receiver, shown in FIG. 3.
Complexity reduction is achieved with the D-SMC method by computing the soft output for each coded bit over only a reduced set of hypotheses. The price paid for this complexity reduction is that the D-SMC suffers from a problem, usually referred to as the “missing candidate problem”, in that the hypotheses (or candidates) necessary for computing the soft outputs for some of the bits may not be present in the reduced set. This missing candidate problem can cause significant degradation in the performance particularly if the reduced set is relatively small compared to the set of all hypotheses. Heuristic techniques to alleviate this problem in the D-SMC have also been proposed but such techniques require a lot of system or scenario specific fine tuning and may not work well under across all conditions.
Referring again to FIG. 2, the D-SMC method 20 involves listing out a subset of possible pairs of symbols 1 and 2 for the two streams received 21, evaluating the metric for each pair 22, using the metrics to determine the approximate max-log LLRs for all bits 23 and decoding the codeword(s) using the computed LLRs 24. Although the D-SMC reception method has tunable complexity, it also has sub-optimal demodulation due to “missing” candidate problem.
In contrast to the D-SMC reception method, the SIC receiver is a sequential receiver where one stream is first decoded and subtracted from the received signal before decoding the second stream. The soft output for the first stream is obtained after assuming the second stream to be a Gaussian interferer which can lead to performance degradation.
Referring again to the FIG. 3, the successive interference cancellation reception method 30 involves suppressing the contribution of symbol-2 via filtering 31, evaluating the metric for all possibilities of symbol-1 32, using the metrics to determine the max-log LLRs for all bits associated with symbol-1 33, decoding the codeword-1 using the computed LLRs 34, re-encoding the codeword which is then modulated and subtracted from the received signal 35, listing out all possibilities for symbol-2 and computing the metrics 36, using the metrics to determine the max-log LLRs for all bits associated with symbol-2 37, and then decoding codeword-2 38.
Accordingly, there is a need for two-stream receivers that are eminently suitable for receivers with low-latency and low complexity necessary to meet the ambitious spectral efficiency targets set for Evolved-UMTS Terrestrial Radio Access (EUTRA).